Adaptive instrument and operator control recognition

ABSTRACT

A system and method of acquiring information from an image of an instrument panel of a vehicle in real time wherein at least one imaging device with advanced light metering capabilities is placed aboard a vehicle, a computer processor means is provided to control the imaging device and the advanced light metering capabilities, the advanced light metering capabilities are used to capture an image of at least a portion of the instrument panel, such as a gauge or operator control, and image recognition algorithms are used to identify the current state of the imaged portion of the instrument panel.

BACKGROUND OF THE INVENTION

1. Field of the Invention

This invention relates to the field of optical instrument recognition,and more particularly to a system and method for automaticallyinterpreting and analyzing gauges, readouts, and the position and stateof user controls in an environment with highly dynamic lightingconditions.

2. Description of the Related Art

The recording and automated analysis of image data is well known in theprior art. For example, optical character recognition, or OCR, is theprocess of analyzing an image of a document and converting the printedtext found therein into machine-editable text. OCR programs are readilyavailable and often distributed for free with computer scanners and wordediting programs. OCR is a relatively simple task for modern softwaresystems, as documents are typically presented with known lightingconditions (that is, an image of dark text on a light background,captured with the consistent, bright exposure light of a documentscanning system) using predetermined character sets (that is, known andreadily-available character fonts).

Systems attempting to recognize handwritten text have the addedchallenge of handling the variations in personal handwriting styles fromone person to the next. Still, these systems often require that thewriters print the text instead of using cursive and that they followcertain guidelines when creating their printed characters. Even in thesesystems, where the individual style variations must be accounted for,the lighting conditions used to capture the text images arewell-controlled and consistent.

Another example of automated image analysis is facial recognition. Afacial recognition system is a computer application for automaticallyidentifying a person from a digital image of the person's face. Facialrecognition programs are useful in security scenarios, such as analyzingpassengers boarding an aircraft in an attempt to identify knownterrorists. A typical facial recognition program works by comparingselected facial features from the image, such as the distance betweenthe person's eyes or the length of the nose, against a facial featuredatabase. As with optical character recognition, facial recognitionworks best in controlled lighting conditions when the subject matter(that is, the face) is in a known orientation relative to the image.

It is also common to use video cameras in the cockpit of an aircraft orcab of a land-based vehicle as a means of gathering data. In the eventof a crash or near-miss, the recorded video can be post-processed (thatis, processed by experts and systems off-board the vehicle, after theimage data has been downloaded to an external system) to determine whatconditions were present in the vehicle during the incident. Storing thevideo data on board the vehicle requires a large amount of storagespace. Because of this, mechanisms are often used to limit the amount ofstorage required on board the vehicle, such as only storing the mostrecent video data (for example, only storing the most recent 10 minutesof data, and overwriting anything older than this.)

The ambient lighting conditions of a vehicle cab or aircraft cockpit arehighly dynamic, and vary based on the time of day, the angle of thevehicle in relation to the sun, and on the presence of other externalsources of illumination. One portion of an instrument panel may beconcealed in shadow, while another portion is bathed in direct sunlight.The dividing line between dark and light constantly changes as thevehicle maneuvers and changes position in relation to the sun.Commercially available camera systems for use in aircraft cockpits donot perform well in these conditions, and provide low-quality images.These limitations make the task of post-processing the image data toclearly identify details within the images difficult if not impossible.

A single clear image of an aircraft cockpit, however, would contain awealth of information about the ongoing flight. An image of a cockpitwould capture a snapshot of the current state of each of the flightinstruments, the position of the pilot and copilot, and the presence ofany unusual conditions (such as smoke) for any given moment in time. Ifautomatic image analysis of this data could be consistently performed inreal time, while the flight is in progress, this visual informationcould be interpreted and stored as numeric data and/or communicated tothe pilot and/or other onboard systems. Further, if this image datacould be captured by a self-contained camera module with built-inprocessing capabilities, the ability to process and analyze cockpitimage data could be added to any vehicle, regardless if that vehicle hadits own onboard computer or sensing systems. This stand-alone cameramodule could capture the image data while the flight or trip was inprogress, analyze the image data and convert it to numeric data, andthen compare that numeric data to pre-existing data, such as a flightplan or terrain model, already contained in the camera module.

What is needed in the art is an imaging system which can, in real time,capture high quality images of an aircraft cockpit or vehicle cab orportions thereof, compensate for the dynamic lighting conditions thatcan be present across even the area covered by a single gauge, analyzethe image data and translate it into numeric data, and provideinformation and/or advisories to the pilots and other onboard systems.This system should also incorporate other information and capabilitiessuch that it is aware of its own position and orientation inthree-dimensional space and such that it can operate as a stand-aloneunit, without the need to be tied into other onboard vehicle systems.

SUMMARY OF THE INVENTION

According to one aspect of the present invention, a method of acquiringinformation from an image of an instrument panel of a vehicle in realtime is provided, comprising the steps of providing at least one imagingdevice with advanced light metering capabilities aboard the vehicle,providing a control means to control the imaging device and advancedlight metering capabilities, using the advanced light meteringcapabilities to capture an image of a portion of the instrument panel,and using image recognition algorithms to identify the current state ofthe corresponding portion of the instrument panel.

According to another aspect of the present invention, a system foracquiring information from an image of an instrument panel of a vehiclein real time is provided, comprising a software-controlled imagingdevice with advanced light metering capabilities, a control means forcontrolling the imaging device and advanced light metering capabilities,a memory module, a GNSS receiver, and an inertial measurement unit. Thecontrol means uses the advanced light metering capabilities to capturean image of a portion of the instrument panel and processes the image toextract information pertaining to the status of the vehicle.

According to yet another aspect of the present invention, asoftware-based rules engine is used to analyze the status informationextracted from the image of the instrument panel in real time todetermine if any of a set of pre-determined rules has been violated, andto initiate an appropriate response if a rule has been violated.

These aspects and others are achieved by the present invention, which isdescribed in detail in the following specification and accompanyingdrawings which form a part hereof.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a front view of a representative instrument panel.

FIG. 2 is a front view of a representative instrument panel as it mightappear to an imaging device when different areas of the panel areexposed to different lighting conditions.

FIG. 3 is a front view of a single gauge showing areas of differentlighting conditions and specular highlights.

FIG. 4A is a high-level block diagram of one embodiment of an adaptiveimaging module that could be used to capture and process images of aninstrument panel.

FIG. 4B is a high-level block diagram showing additional detail on theimaging device component of the adaptive imaging module of FIG. 4A.

FIG. 5 is a perspective view representing a cockpit or vehicle cabshowing the mounting relationship between the adaptive imaging module ofFIG. 4 and the instrument panel of FIGS. 1 and 2.

FIG. 6A is a perspective view of one embodiment of a system for use incalibrating the invention for first-time use in a vehicle cab orcockpit.

FIG. 6B is a flowchart describing one embodiment of a method of settingup and calibrating the invention for first-time use in a vehicle cab orcockpit.

FIG. 6C is a flowchart describing one embodiment of a method ofcapturing fiducial images for use in image alignment.

FIG. 7A shows how the arrangement of the gauges on a given instrumentpanel can be used as a fiducial image that can be used to determine thecorrect alignment of the image.

FIG. 7B shows how certain features on a specific gauge can be used as afiducial image to determine the correct alignment of an image of thecorresponding gauge.

FIG. 7C shows how certain areas of a gauge image may be masked off sothat only the immediate area of interest can be focused on.

FIG. 8 is a flowchart describing one embodiment of a method foracquiring image data from an instrument panel using the imaging moduleof FIG. 4.

FIG. 9 is a flowchart describing one embodiment of a method forretrieving and processing numeric data from images of an instrumentpanel.

FIG. 10 is a flowchart describing one embodiment of a method for usingnumeric data as acquired and described in FIG. 9 to generate real-timeinformation about the trip or flight in process.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

With reference now to the drawings, and in particular to FIGS. 1 through10 thereof, a new adaptive instrument recognition process and deviceembodying the principles and concepts of the present invention will bedescribed.

FIG. 1 is a front view of a representative instrument panel 10. For thepurposes of this discussion, an “instrument panel” shall be defined as afixed arrangement of gauges, lights, digital readouts, displays, anduser controls as might be seen in the cab of a vehicle, such as a car ortruck, or in the cockpit of an aircraft. The depiction of the instrumentpanel 10 in FIG. 1 is meant to be illustrative of the type and style offeatures as might be seen in any type of vehicle, and not meant to belimiting in any way. The features shown in FIG. 1 are suggestive ofthose that might be seen on an aircraft such as a helicopter, but thepresent invention will work equally well on any type of instruments inany type of vehicle. In addition, for the purposes of this discussion,any gauge, display, operator control, or input device that is located inthe vehicle cab or aircraft cockpit, and which can be detected andcaptured in an image, will be considered to be a part of the instrumentpanel, even if it is not physically attached to other features in thecab or cockpit. For example, the position of the flight yoke used by theoperator of the aircraft can be captured in an image of the cockpit, andwill be considered to be part of the instrument panel as defined herein.

An instrument panel 10 offers a user interface to the operator of avehicle. Information may be presented to the operator in the form ofgauges 100, which provide data as to the operating status of variousvehicle systems. These gauges 100 are typically mechanical in nature(for example, a mechanical fuel gauge with a needle indicating the levelof fuel in the fuel tank), incapable of storing the information theypresent long-term, and only provide an instantaneous snapshot of thesystems they are monitoring. An instrument panel 10 may also use one ormore status lights 110 to indicate the presence or absence of acondition. For example, a “low fuel” light may illuminate when theamount of fuel in the fuel tank has reached a pre-set lower limit.

Alternative embodiments of an instrument panel may exist which offerfeatures for presenting information to the operator other than thoseshown in FIG. 1. As one example, an alternative embodiment of aninstrument panel may include digital readouts which provide numericinformation to the operator instead of offering the information in theform of a gauge. It is obvious to one skilled in the art that anyfeature that provides information to an operator in the form of avisible indication that can be detected in an image or visually by theoperator could be used with the present invention.

In addition to providing information to the operator, an instrumentpanel 10 may offer one or more operator controls by which an operatorcan provide input or control a feature of the vehicle. For example, aninstrument panel 10 may offer one or more rotary knobs 120 as a means ofadjusting or calibrating one of the gauges 100. Functional switches 130may also be offered to allow the operator to enable and disable vehiclefunctions.

Alternative embodiments of an instrument panel may exist which offerfeatures for operator input other than those shown in FIG. 1. Forexample, an alternative embodiment of an instrument panel may include alever, slide, or a multi-position switch. It is obvious to one skilledin the art that any feature through which an operator can input controlinformation into the vehicle or instrument panel, and for which theposition or status can be detected visually in an image or by theoperator could be used with the present invention.

FIG. 2 is a front view of the representative instrument panel 10 of FIG.1 as it might appear to an operator or imaging device when differentareas of the panel are exposed to different lighting conditions. As avehicle moves, the instrument panel 10 is exposed to various lightingconditions depending on many factors, including the angle of the vehiclein relation to the sun, the time of day, and the presence of otherexternal sources of illumination. Portions of the instrument panel 10may be bathed in bright light 200, while other portions of theinstrument panel 10 may be obscured by light shadow 210 or dark shadow220. The boundaries between the areas of bright light 200, light shadow210, and dark shadow 220 are constantly changing. It is likely thatthese boundaries between lighting conditions may at some point fallacross the face of one or more gauges 100, status lights 110, rotaryknobs 120, or functional switches 130, or any other type of feature thatmay be present on the instrument panel 10. These dynamic lightingconditions make it difficult for imaging devices to produce clear,readable images of the instrument panel 10 and its features.

FIG. 3 is a front view of a single gauge 100 showing areas of differentlighting conditions and specular highlights. A typical gauge 100presents information to the operator through the use of a needle 300.The position of the needle 300 against a graduated scale of tick marks350 or other indicia provide status information, such as the currentairspeed or altitude, to the operator. Just as the instrument panel 10is subject to the presences of dynamic lighting conditions, as shown inFIG. 2, a single gauge 100 may itself be subject to these varyingconditions. While one portion of the gauge 100 is in bright light 310,other portions may be in light shadow 330 or dark shadow 320. As a gauge100 typically has a glass or clear plastic faceplate, the face of thegauge 100 may also be subject to the presence of one or more specularhighlights 340. A specular highlight 340 is a bright spot of light thatappears on a glossy surface, the result of the reflection of an externalsource of light. This specular highlight 340 may obscure at least aportion of the needle 300 or the tick marks 350, which can be asignificant obstacle for image processing.

The use of a gauge 100 featuring a needle 300 and tick marks 350 in FIG.3 is meant to be illustrative and should not be construed as limiting inany way. Any other appropriate type of gauge, such as a compassfeaturing the graphic of an aircraft rotating to show the true headingof the actual aircraft instead of a needle, may be subject to theselocalized dynamic lighting effects and applicable to the presentinvention. In addition, other features presenting information to theoperator (such as status lights, digital readouts, or computer displays)or operator controls receiving input from an operator (such as levers,knobs, switches, and pushbuttons) would be affected by the localizeddynamic lighting as described herein.

FIG. 4A is a high-level block diagram of one embodiment of an adaptiveimaging module 40 that could be used to capture and process images of aninstrument panel 10 such as the one shown in FIG. 1 and FIG. 2. In thepreferred embodiment, the adaptive imaging module 40 includes an imagingdevice 400, such as a CCD camera or CMOS camera or any other appropriateimaging system. The imaging device 400 is used to acquire images of allor part of the instrument panel 10, a process that is further describedin FIGS. 6B, 8, and 9. Additional detail on the components of theimaging device 400 itself is also provided in FIG. 4B. Integrated intothe adaptive imaging module 40 along with the imaging device 400 are aGlobal Navigation Satellite System (GNSS) receiver 410 and an inertialmeasurement unit (IMU) 440. GNSS is the generic term for satellitenavigation systems that provide autonomous geo-spatial positioning withglobal coverage, an example of which is the Global Positioning System(GPS) developed by the United States Department of Defense. The GNSSreceiver 410 receives signals from an appropriate satellite system andcalculates the precise position of the adaptive imaging module 40 inthree-dimensional space (latitude, longitude, and altitude). An IMU is adevice used for sensing the motion—including the type, rate, anddirection of that motion—of an object in three-dimensional space. An IMUtypically includes a combination of accelerometers and gyroscopes tosense the magnitude and rate of an object's movement through space. Theoutput of the IMU 440 and the GNSS receiver 410 are combined in theadaptive imaging module 40 to calculate the precise location andorientation of the adaptive imaging module 40 in three-dimensionalspace. This location/orientation information can be paired with specificimages captured by the imaging device 400 to create a record of where avehicle was located in space when a specific image was captured.

The adaptive imaging module 40 contains a processor 460 which performsall image recognition and control functions for the adaptive imagingmodule 40. The processor 460 has sufficient computing power and speed,at a minimum, to perform the set-up functions described in the flowchartof FIG. 6B, to perform the image acquisition functions described in theflowchart of FIG. 8, to perform the image processing functions describedin the flowchart of FIG. 9, to perform the flight operations functionsdescribed in the flowchart of FIG. 10, and to perform all powermanagement, input/output, and memory management functions required bythe adaptive imaging module 40.

Data acquired during a trip, including but not limited to image andvideo data, position and orientation data, sound and intercom systemdata, and other miscellaneous trip parameters, is stored inside theadaptive imaging module 40 in a memory module 430 which is optionallyhardened to allow survivability in the event of a vehicle crash. Such acrash-hardened memory module is disclosed in U.S. Patent Publication No.2008/0074854 for Crash-Hardened Memory Device and Method of Creating theSame, which is assigned to a common assignee herewith and isincorporated herein by reference. An optional removable memory device470 provides back up for the memory module 430 as well as a means oftransferring data from the adaptive imaging module 40 to an off-boardsystem (not shown and not part of this invention). The removable memorydevice 470 may be any appropriate portable memory media, including butnot limited to SD or MMC memory cards, portable flash memory, or PCMCIAcards.

The preferred embodiment of the adaptive imaging module 40 also containsa communications port 420 that can be used as an alternative means fortransferring data to an off-board system or as a means of uploadingfirmware updates, trip profile information, configuration data or anyother appropriate type of information. The communications port 420 maybe implemented with any appropriate communications protocol or physicallayer, including but not limited to ethernet, RS232, CAN (controllerarea network), USB (universal serial bus), or an industry standardprotocol such as ARINC 429 or 629, as used in aviation.

The adaptive imaging module 40 has a power supply 480 which providespower to the on-board systems and functions. The power supply 480 may beconnected directly to vehicle power or to an alternative energy sourcesuch as a battery.

Optionally, the adaptive imaging module 40 has a sound and intercomsystem interface 450 which is tied into an on-board cabin microphonesystem and/or vehicle intercom system. The sound and intercom systeminterface 450 allows the adaptive imaging module 40 to record ambientcabin sound and/or verbal communications made by the vehicle operators.

FIG. 4B is a high-level block diagram showing additional detail on theimaging device component of the adaptive imaging module of FIG. 4A. Theimaging device 400 contains an imaging sensor 405, a sensor controller415, an image processing subsystem front end 425, and an imageprocessing subsystem back end 435. The imaging sensor 405 is a devicethat converts an optical image to an electrical signal. The imagingsensor 405 may be a charge-coupled device (CCD), a complementarymetal-oxide-semiconductor (CMOS) active-pixel sensor, or any otherappropriate imaging sensor. A CCD imaging sensor uses a lens to projectan image onto a special photoactive layer of silicon attached to acapacitor array. Based on the light intensity incident on a region ofthe photoactive layer, the corresponding capacitors in the arrayaccumulate a proportional electrical charge, and this array ofelectrical charges is a representation of the image. A CMOS device, onthe other hand, is an active pixel sensor consisting of an array ofphoto sensors (active pixels) made using the CMOS semiconductor process.Circuitry next to each photo sensor converts the light energy to acorresponding voltage. Additional circuitry on the CMOS sensor chip maybe included to convert the voltage to digital data. These descriptionsare provided as background only and are not meant to infer than theimaging sensor is limited to being either a CCD or CMOS device. Asillustrated by the examples described in the previous paragraph, theimaging sensor 405 is used to capture raw pixel information, whereineach pixel captured represents a corresponding brightness level detectedfrom an area of an object. A sensor controller 415 controls thefunctions of the imaging sensor 405, including, among other things, theexposure time of the imaging sensor 405 (that is, the duration for whichthe imaging sensor 405 is allowed to be exposed to the light beingreflected or cast from an environment). The sensor controller 415 thentransfers the raw pixel data from the imaging sensor 405 to an imageprocessing subsystem front end 425. The image processing subsystem frontend 425 contains a preview engine 425A and a histogram 425B. The previewengine 425A temporarily receives the raw pixel data so that it can beanalyzed and processed by the sensor controller 415. The histogram 425Bis a buffer area that contains information related to the relativebrightness of each pixel, stored as a number of counts (that is, adigital number representing the magnitude of the analog brightness valueof each pixel). The sensor controller 415 analyzes the count valuescontained in the histogram 425B and determines if certain areas ofpixels are overexposed or underexposed, and then directs the imagingsensor 405 to change its exposure time appropriately to adjust thebrightness levels obtained.

The image processing subsystem front end 425 allows the imaging device400 to perform advanced light metering techniques on a small subset ofthe captured pixels, as opposed to having to perform light metering onan entire image. For the purpose of this document, the phrase “advancedlight metering techniques” shall be defined as any light meteringtechniques, such as those typically used in digital photography, whichcan be applied to a selected portion of an object to be imaged asopposed to the object as a whole, and which can be tightly controlled bya software program or electronic hardware. The advanced light meteringtechniques used in the present invention are further described in FIG. 8and in the corresponding portion of this specification.

This advanced light metering capability, among other things,distinguishes the present invention over the existing art. If thedynamic lighting conditions as described in FIG. 3 are present, oneportion of a gauge 100 or other feature of an instrument panel 10 may bein bright light 310 while another may be in dark shadow 320, forexample.

Existing prior art camera systems have very limited light meteringcapabilities, if any, and must be preconfigured to focus on one type oflight condition. If a prior art camera system is adjusted to captureimages based on light conditions typical to the interior of a vehicle,the scenery that would otherwise be visible outside the vehicle (throughthe windscreen or windshield) will be washed out and indiscernible.Conversely, if a prior art camera system is adjusted to capture imagesof the outside world, images from inside the vehicle, such as theinstrument panel, will be too dark and unreadable.

The advanced light metering capabilities of the present invention allowit to adjust for varying light conditions across a small subset of imagepixels, selecting one light meter setting for one area of pixels andanother setting for a different area of pixels. In this manner, specularhighlights 340 and areas of different ambient light intensity (310, 320,and 330) can be compensated for and eliminated to create a single imageof a gauge 100 or other feature of unparalleled quality.

Once the raw pixel data has been captured and corrected by the imageprocessing subsystem front end 425, the corrected pixel data is sent toan image processing subsystem back end 435, which contains an imageencoder 435A. The image encoder 435A is a device that is used to convertthe corrected pixel data into an image file in a standard image fileformat. A JPEG encoder is one type of image encoder 435A that is used tocreate images in the industry standard JPEG file compression format. Anyother appropriate image file format or encoder could be used withoutdeviating from the scope of the invention.

In the preferred embodiment, the image processing subsystem back end 435is an optional component, as the imaging device 400 will normally workdirectly with the raw image data that is created as a product of theimage processing subsystem front end 425, without requiring the standardimage file output by the image processing subsystem back end 435.However, the image processing subsystem back end 435 is included in thepreferred embodiment to allow the imaging device 400 to output images instandard file formats for use in external systems (not described hereinand not considered part of the present invention).

FIG. 5 is a perspective view representing a cockpit or vehicle cab 50showing the mounting relationship between the adaptive imaging module 40of FIG. 4 and the instrument panel 10 of FIGS. 1 and 2. The adaptiveimaging module is mounted in the cockpit or vehicle cab 50 such that itcan capture images of the instrument panel 10. The adaptive imagingmodule 40 is typically mounted above and behind a vehicle operator 500,in order to be able to capture images from the instrument panel 10 withminimum interference from the vehicle operator 500. However, theadaptive imaging module 40 may be mounted in any appropriate locationwithin the cockpit or vehicle cab 50.

Referring now to FIGS. 6A, 6B, and 6C a system for use in calibratingthe invention for first-time use in a specific vehicle cab or cockpitwill be described. A computer 605 hosting a set-up utility 615 isconnected via a data connection 625 to the adaptive imaging module 40.The computer 605 may be a laptop, tablet or desktop computer, personaldigital assistant or any other appropriate computing device. The dataconnection 625 may be a hardwired device-to-device connection directlyconnecting the computer 605 to the adaptive imaging module 40, awireless interface, an optical connection such as a fiber optic cable ora wireless infrared transmission method, a network connection includingan internet connection, or any other appropriate means of connecting thetwo devices together such that data can be exchanged between them. Theset-up utility 615 is a software application that is executed before theadaptive imaging module 40 can be used for the first time on a new typeof instrument panel 10. The purpose of the set-up utility 615 is toallow an operator to identify the location, significance, and datapriority of each feature of an instrument panel 10. In the preferredembodiment, this process is done as described in the flowchart of FIG.6B.

The adaptive imaging device 40 is used to acquire a test image 600A ofthe instrument panel 10 [Step 600]. Ideally, the test image 600A iscaptured in controlled lighting conditions such that a crisp, cleanimage of the instrument panel 10 is captured for the set-up process. Theoperator of the set-up utility 615 identifies the location within thetest image 600A of each object of interest, which may be a gauge 100,status light 110, rotary knob 120, functional switch 130 or any othervisually discernible feature on the instrument panel 10 [Step 610].Throughout the remainder of this specification, the term “object ofinterest” shall be used as a general term to refer to these visuallydiscernible features (gauges, lights, knobs, levers, etc.) seen in animage within the vehicle, and which are the target of the processingdescribe herein.

For each object of interest on the instrument panel 10 or elsewhere, itmust be determined if the object is on a list of known object types inan object library, or if a new object type must be created for thecorresponding feature [Step 620]. In one embodiment of the invention,Step 620 is performed manually by the operator of the set-up utility615. In an alternative embodiment, Step 620 is performed automaticallyusing optical recognition techniques to attempt to match the object ofinterest to an object type in the object library. If the object ofinterest from the test image 600A already exists in a predefined libraryof similar objects, the set-up utility 615 allows the operator to reviewthe default configuration for that object type and accept it as is ormake modifications to it [Step 630]. Once the object type is accepted bythe operator, the set-up utility 615 stores the configuration data forthat feature of the instrument panel 10 in a configuration file 600B forthat specific instrument panel for future use [Step 670].

If, on the other hand, the object of interest is found not to exist in alibrary of pre-defined objects in Step 620, the operator must manuallyidentify the object type [Step 640]. For example, the operator maydetermine the object of interest is a 3-Inch Altimeter Indicator, partnumber 101720-01999, manufactured by Aerosonic. The operator must thenidentify the possible range of movement of the needles (which, for analtimeter, would be a full 360 degrees) and identify the upper and lowervalues for each needle, as well as the increment represented by eachtick mark on the altimeter image [Step 650]. Optionally, the operatormay identify graphics or features on the object of interest, such as theletters “ALT” on an altimeter, which could be used as “fiducial” marksfor later image alignment [Step 660]. For the purposes of thisdiscussion, the term “fiducial” shall be defined as a fixed standard ofreference for comparison or measurement, as in “a fiducial point”, thatcan be used in the image alignment process. Once the new object ofinterest type is fully defined by Steps 640 through 660, the new objecttype is stored in a configuration file 600B for future use [Step 670].The set-up process defined in FIGS. 6A and 6B should only need to beperformed once for each aircraft or vehicle type, assuming there is alarge percentage of common features for each vehicle of that type. Afterthat, the object type information stored in the configuration file 600Bfor that aircraft type should be sufficient. This configuration file600B is uploaded and stored in the on-board memory module 430 of theadaptive imaging module 40, so that it can be retrieved as needed duringin-trip image processing.

FIG. 6C is a flowchart describing one embodiment of a method ofcapturing fiducial images for use in image alignment. The operator ofthe set-up utility 615 uses the test image 600A to create anoutline-only version of the of the instrument panel 10 [Step 655],referred to herein as a panel fiducial image 700, and furtherillustrated in FIG. 7A. This panel fiducial image 700 consists ofoutline drawings of each feature on the instrument panel 10, includingbut not limited to gauge outlines 720, status light outlines 730, andoutlines of functional switches 740, as well as an outline of theenclosure of the instrument panel itself 710. These outlines can becreated in a manual process, where the operator uses the set-up utility615 to manually draw outlines around the features of the instrumentpanel. This manual process may be aided or replaced entirely by a simpleedge-detection algorithm, a standard image processing algorithm used toautomatically detect the abrupt edges in an image found at the interfacebetween one feature and the next. Edge detection algorithms are wellknown in the art.

The purpose for creating a panel fiducial image 700 is to aid indetermining the proper alignment of the images captured by the adaptiveimaging module 40. Because the spatial relationship between features inthe panel fiducial image 700 are fixed, this relationship can be used todetermine the angle of a given gauge image. For example, the adaptiveimaging module 40 captures an image of the entire instrument panel 10.Because the adaptive imaging module 40 and the instrument panel 10 areindependently mounted (mounted to different structures within thevehicle), and further because the instrument panel 10 is oftenspring-mounted in some vehicles, the angle of the adaptive imagingmodule 40 to the instrument panel 10 is constantly changing. One imagetaken of the instrument panel 10 may be at a slightly different anglethan an image taken only moments later. This becomes a problem for animage analysis algorithm that is trying to determine the angle of aneedle on a gauge to determine that gauge's reading. However, therelationship among the various features integral to the instrument panel10 is constant. The panel fiducial image 700 can be used as a templateagainst which to compare each new image taken. An image analysisalgorithm can continue to estimate the angle of the new image until itis aligned with the panel fiducial image 700.

Similarly, the set-up utility 615 can be used to create a fiducial imageof each individual object of interest in the test image 600A [Step 665of FIG. 6C]. An example “feature fiducial image” 705 is shown in FIG.7B. The operator uses the set-up utility 615 to identify items on thefeature fiducial image 705 which can later be used for image alignmentpurposes. These items may include tick marks 310, gauge graphics 715, orany other appropriate item on the face of the object of interest, theposition of which is fixed and constant in relation to the face of theobject of interest.

Finally, the set-up utility 615 is used to identify and create a featuremask 725 for each object of interest [Step 675 of FIG. 6C]. An examplefeature mask 725 is shown in FIG. 7C. For most of the objects ofinterest in a given instrument panel 10, there is only a small part ofthe image of that object which is actually needed to determine the exactstate of the object of interest. For example, for a given mechanicalgauge, such as the one shown in FIG. 7C, only a small unmasked region745 for that gauge is needed to determine the value shown on that gauge.If the gauge image has already been aligned properly (using the panelfiducial image and the feature fiducial images of FIGS. 7A and 7B), thetick marks 310 on the gauge are unimportant, as they are a feature thatcannot change from one properly aligned image to the next.

The operator uses the set-up utility 615 to identify the unmasked region745 for each specific object of interest. This may be done by drawing anoutline around a portion of the image of each object of interest tocreate the unmasked region 745, or by selecting a pre-defined masktemplate from an existing library. For the illustrative example in FIG.7C, a portion of the gauge needle 735B falls within the unmasked region745, and another portion 735A falls outside of the unmasked region 745.Only the 735B needle portion is necessary to determine the angle of theentire needle in relation to the gauge itself.

This feature mask 725 is used during the spot metering process describedin FIG. 8. The feature mask 725 defines an “area of interest” on whichthe spot metering process can be applied. This spot metering process isdescribed in more detail later in this specification.

The panel fiducial image 700, feature fiducial image 705, and featuremask 725 are stored in the configuration file 600B for the instrumentpanel, which is itself stored in the memory module 430 of the adaptiveimaging module 40. The configuration file 600B is retrieved as neededduring the image acquisition process shown in FIG. 8. It should be notedthat the term “configuration file”, as used herein, shall refer to acollection of configuration data items that may actually be physicallystored in more than one file, or in more than one physical location.

FIGS. 7B and 7C are illustrative only and show a mechanical gauge as anexample for creating the feature fiducial images 705 and feature masks725. Any other appropriate object of interest, such as a status light110, rotary knob 120, or functional switch 130 may also be used tocreate feature fiducial images 705 and feature masks 725. For example,the feature fiducial image 705 for a functional switch 130 may use thelettering beneath the functional switch 130 as the fiducial foralignment purposes.

Once the calibration processes described above in FIGS. 6A through 7Care completed, the adaptive imaging module 40 may be used to acquire andanalyze images during an actual trip. FIG. 8 is a flowchart describingone embodiment of a method for acquiring image data from an instrumentpanel 10 using the adaptive imaging module 40. The adaptive imagingmodule 40 determines on which object of interest it should beginprocessing [Step 800] by reviewing the configuration file 600B stored inthe memory module 430. The configuration file 600B contains theconfiguration data specific to each object of interest, including theobject's location in the instrument panel 10, the panel fiducial image700, and the corresponding feature fiducial image 705 and feature mask725 for that object.

Using the data retrieved from the configuration file 600B, the adaptiveimaging module 40 uses software-controlled light metering capabilitiesto control the settings of the imaging device 400 such that a clearimage of the object of interest can be captured [Step 810]. The adaptiveimaging module 40 is capable of using advanced metering techniquesincluding but not limited to spot metering (that is, taking a meterreading from a very specific, localized area within an object ofinterest), average metering (that is, taking a number of meter readingsfrom different locations within an object of interest and averaging thevalues to obtain a file exposure setting), and center-weighted averagemetering (that is, concentrating the metering toward the center 60 to80% of the area to be captured). Because each object of interest has anassociated feature mask 725 which isolates the portion of the objectthat should be imaged, the adaptive imaging module 40 can concentrateits light metering efforts on only that area, eliminating much of theconcern of dealing with large areas of dynamic lighting conditions suchas those shown in FIG. 2.

Finally, an image is captured of the object of interest or of the areadefined specifically by the object's feature mask 725 [Step 820]. Thisprocess is repeated as necessary for each object of interest. Raw imagedata 900A is created for each object of interest, and this raw imagedata 900A is processed as described in FIG. 9.

FIG. 9 is a flowchart describing one embodiment of a method forretrieving and processing numeric data from images of an instrumentpanel. Once the raw image data 900A is acquired by the adaptive imagingmodule 40, a low-pass filter is applied to remove image noise [Step 900]to create a reduced noise image 900B. Edge detection is performed on thereduced noise image 900B [Step 910] to create an edge-only image 900C.As used in this document, the term “edge detection” refers to the use ofan algorithm which identifies points in a digital image at which theimage brightness changes sharply or has detectable discontinuities. Edgedetection is a means of extracting “features” from a digital image. Edgedetection may be performed by applying a high pass filter to the reducednoise image 900B, by applying an image differentiator, or by anyappropriate method. An example of an edge detection algorithm isdisclosed in U.S. Pat. No. 4,707,647 for Gray Scale Vision Method andSystem Utilizing Same, which is incorporated herein by reference.

A binary hard-limiter is applied to the edge-only image 900C to convertit to a binary (black and white) image 900D [Step 920]. The binary image900D is then cross-correlated against fiducial images (such as the panelfiducial image 700 and feature fiducial image 705) to bring the imageinto correct alignment [Step 930], creating an aligned binary image900E. Optionally, a mask such as the feature mask 725 may be applied tothe aligned binary image 900E to create a masked binary image 900F [Step940]. Creating the masked binary image 900F would eliminate all but themost crucial portion of the aligned binary image 900E in order tosimplify processing.

The masked binary image 900F is now processed to determine the needleposition 900G in relation to the gauge [Step 950]. This processing maybe done in a number of ways. In one embodiment, synthetic images of thegauge face (or the pertinent portion thereof, if the image is masked)are generated, each drawing the needle in a slightly different position.These synthetic images are compared to the masked binary image 900Funtil a match is found. When the match is found, the angle of the needlein the synthetic image matches the actual needle angle. In analternative embodiment, linear regression is used to find the needle,which consists of doing a least squares line fit to all the points(pixels) that come out of the masked binary image to determine theneedle position 900G. Any other appropriate processing method can beused.

Finally, the gauge value 900H is determined based on the needle position900G [Step 960]. This is done by retrieving the upper and lower limitsand range of travel information for the needle for the correspondingobject type from the configuration file 600B from the memory module 430and comparing the current needle position 900G to those values.

The use of the term “needle” in FIG. 9 is meant to be illustrative only,and should not be considered to limit the process only to images ofmechanical gauges. For the purposes of FIG. 9, the term “needle” can besaid to refer to any moving or changing part in an image, and mayequally refer to the position of a switch or lever or the condition(illuminated or not illuminated) of a light, or the position or statechange of any other appropriate feature on an instrument panel 10.

FIG. 10 is a flowchart describing one embodiment of a method for usingnumeric data as acquired and described in FIG. 9 to generate real-timeinformation about the trip or flight in process. Because the adaptiveimaging module 40 contains a GNSS receiver 410 and an inertialmeasurement unit (IMU) 440, additional functionality can be achievedwhich cannot be achieved with a stand-alone imaging device 400. Thegauge value 900G determined in Step 960 can be combined with locationand orientation data from the GNSS receiver 410 and the IMU 440 tocreate a fused sensor value 1000A [Step 1000]. For the purposes of thisdiscussion, the term “fused sensor value” shall refer to a set of dataconsisting of, at a minimum, a time/date stamp, the location andorientation of the vehicle in three-dimensional space corresponding tothe time/date stamp, and the value of the gauge (or other object ofinterest) corresponding to the time/date stamp.

This fused sensor value 1000A is then processed by an on-board rulesengine [Step 1010]. The rules engine is a software application whichcontains a terrain model (containing information on the surroundingterrain), a set of predefined trip profiles (rules applied to certaintypes of vehicles to ensure safe or efficient use), or a combination ofthe two. This rules engine can be used to determine if a situationexists that should be communicated to the operator or a base station, orwhich may automatically initiate an action in response to the situation.In Step 1020, the rules engine analyzes the fused sensor value 1000A todetermine if an exceedance was generated. For the purposes of thisdiscussion, an “exceedance” shall be defined as any condition that isdetected that either violates a defined trip profile or results in anunsafe situation. For example, the rules engine may contain a flightprofile for an aircraft that specifies that a rapid descent below 500feet in altitude is dangerous. When the adaptive imaging module 40detects that the aircraft is in violation of this flight profile (whichit does by comparing the fused sensor values 1000A obtained from thealtimeter, airspeed indicator, and vertical airspeed indicator), anexceedance would be generated. In another example, an exceedance may begenerated when the fused sensor value 1000A for the altimeter indicatesthat the aircraft is getting too close to the ground (based on a modelof the surrounding terrain embedded within the rules engine).

If no exceedance is generated, the process returns to Step 960 and isrepeated. If, however, an exceedance was generated, an event 1000B istriggered and recorded [Step 1030]. For the purposes of this discussion,an “event” will be defined as the result of a specific exceedance, andmay consist simply of a recorded message being stored in memory forlater retrieval, or may trigger an action within the vehicle (such asthe sounding of an audible alarm or the illumination of a warning icon).

Optionally, the generated event 1000B and other data may be transmittedoff-board via a wide area network such as a telemetry device [Step1040]. For the purposes of this document, a telemetry device shall bedefined to be any means of wireless communication, such as transmissionover a satellite or cellular telephone communications network, radiofrequency, wireless network, or any other appropriate wirelesstransmission medium. The generated event 1000B may optionally triggerthe recording of video by the adaptive imaging module 40 for apre-determined duration [Step 1050] in order to capture activity in thecockpit or vehicle cab corresponding to the event.

The process described in FIG. 10 can be used in a flight operationsquality assurance (FOQA) program. An example of such a FOQA program isdisclosed in U.S. Patent Publication No. 2008/0077290 for FleetOperations Quality Management System, which is assigned to a commonassignee herewith and is incorporated herein by reference. A FOQAprogram, also known as Flight Data Management (FDM) or Flight DataAnalysis, is a means of capturing and analyzing data generated by anaircraft during a flight in an attempt to improve flight safety andincrease overall operational efficiency. The goal of a FOQA program isto improve the organization or unit's overall safety, increasemaintenance effectiveness, and reduce operational costs. The presentinvention allows a FOQA program to be easily applied to an aircraft orfleet of aircraft. The adaptive imaging module 40 does not require anylogical connection to an aircraft's existing systems, and can be used onan aircraft that does not have electronic systems or computer control.All necessary data required to implement the FOQA system can be acquiredfrom the image data captured from an aircraft cockpit as describedherein. The rules engine of Step 1010 can encode the flight profiles forthe aircraft types being tracked by a particular FOQA program.

Preferably all processing required by the system can be completed inreal time. For the purposes of this document, the phrase “real time”shall be interpreted to mean “while a vehicle is being operated” or“while the vehicle is in motion”. The system also preferablyaccommodates individual metering control of a small area (subset) ofimage pixels for processing and use in a self-contained on-board FOQAsystem, as described herein. The present invention can be usedcompletely in real time (during the trip of a vehicle), is fullyself-contained, and does not require post-processing.

Having described the preferred embodiments, it will become apparent thatvarious modifications can be made without departing from the scope ofthe invention as defined in the accompanying claims. In particular, theprocesses defined within this document and the corresponding drawingscould be altered by adding or deleting steps, or by changing the orderof the existing steps, without significantly changing the intention ofthe processes or the end result of those processes. The examples andprocesses defined herein are meant to be illustrative and describe onlyparticular embodiments of the invention.

1. A method of acquiring information from an image within a vehiclecomprising the steps of: providing at least one imaging device aboardsaid vehicle, wherein said imaging device comprises individual raw pixelelements; providing a computer processor to control said imaging device;capturing image data representing an area within said vehicle using saidraw pixel elements with said imaging device; applying one or moreadvanced light metering techniques to at least a subset of said rawpixel elements to create adjusted raw pixel elements; converting saidadjusted raw pixel elements to an image; inputting said image to saidcomputer processor; identifying with said computer processor a state ofsaid image; and said computer processor providing an outputcorresponding to said image state.
 2. The method of claim 1 wherein allsteps are performed in real time while said vehicle is in operation. 3.The method of claim 1 further comprising the steps of: analyzing saidimage state with a rules engine executing on said computer processor;determining if said image state indicates that said vehicle is inviolation of a condition defined by said rules engine; and initiating anappropriate response to said violation.
 4. The method of claim 3 whereinsaid rules engine comprises aircraft flight profile rules as used by aflight operations quality assurance (FOQA) program.
 5. The method ofclaim 3 wherein said step of initiating an appropriate response includesat least one of: sounding an aural alarm; displaying a visual alarm; andreporting the condition to an off-board station by means of a telemetrydevice.
 6. The method of claim 1, which includes the steps of: providingsaid imaging device with advanced light metering capabilities chosenfrom among the group comprising spot metering, average metering andcenter-weighted average metering; and controlling said light meteringcapabilities with said computer processor.
 7. The method of claim 6wherein said step of using advanced light metering capabilities tocapture an image further includes applying said advanced light meteringcapabilities directly to raw pixel data before an image file is created.8. The method of claim 1 wherein said image includes an object ofinterest comprising at least a portion of an instrument panel of saidvehicle.
 9. The method of claim 8 wherein said at least a portion ofsaid instrument panel is a feature selected from the group comprising:mechanical gauge, digital readout, status light, functional switch,computer display, and operator control.
 10. The method of claim 1, whichincludes the steps of: calibrating the imaging device with an adaptiveimaging module; acquiring a test image of an object of interest withsaid adaptive imaging module; and identifying coordinates for saidobject of interest in said test image.
 11. The method of claim 10, whichincludes the steps of: providing an object library comprisinginformation corresponding to images of pre-identified objects ofinterest; determining if an object of interest is included in the objectlibrary; if said object of interest is found in the object library,storing the object of interest configuration from said object librarywith said computer processor; and if said object of interest is notfound in the object library, identifying and storing its configurationand operational characteristics with said computer processor.
 12. Themethod of claim 11 wherein said object library includes pre-identifiedobjects of interest corresponding to specific types of vehicles and saidmethod includes the step of selecting the vehicle type from said objectlibrary.
 13. The method of claim 1, which includes the steps of:providing raw image data of an object of interest from said imagingdevice; applying a low-pass filter to said raw image data to removeimage noise therefrom; using an edge detection algorithm for identifyingpoints in said image data at which the image brightness changes sharplyor has detectable discontinuities; applying a binary hard limiter toconvert an edge-only image to a binary image of said object of interest;and providing an output corresponding to a state of said object ofinterest binary image.
 14. The method of claim 13, which includes thestep of: applying a high-pass filter to perform edge detection on saidimage data.
 15. The method of claim 13, which includes the step of:applying an image differentiator to perform edge detection on said imagedata.
 16. The method of claim 13, which includes the steps of: creatinga fiducial image of an object of interest; storing with said computerprocessor said fiducial image; providing a binary image with saidimaging device; and aligning said binary image detected by said imagingdevice by comparing and cross-correlating said binary image with saidfiducial image.
 17. The method of claim 16, which includes the steps of:applying a mask to said aligned binary image to isolate a portion ofsaid object of interest; said imaging device providing an input to saidcomputer processor corresponding to said isolated portion of said objectof interest; and said computer processor analyzing a state of saidisolated portion of said object of interest and providing acorresponding output.
 18. The method of claim 17, which includes thesteps of: determining a state of the object of interest using either:synthetic images of the isolated portion of the object of interest forcomparison with the masked binary image; or a linear regression to fitthe points (pixels) from the masked binary image to determine the objectof interest state.
 19. The method of claim 1, which includes the stepsof: providing a configuration file for an object of interest with limitsof travel of a moving or changing part of the object of interest; anddetermining an operating condition of the vehicle by comparing theobject of interest binary file with the configuration file.
 20. Themethod of claim 1, which includes the steps of: using a set-up utilityto create a fiducial image comprising multiple individual fiducialimages of multiple objects of interest; and using said set-up utility tocreate a feature mask for each individual object of interest.
 21. Themethod of claim 1, which includes the additional steps of: receivinggeospatial data corresponding to a geospatial position, velocity orattitude of said vehicle; combining said geospatial data with data fromsaid imaging device corresponding to a state of an object of interest insaid vehicle to create a fused sensor value; providing a rules enginecorresponding to operating characteristics of said vehicle; comparingwith said computer processor said fused sensor value with said rulesengine; detecting an exceedance of said rules engine based on saidcomparison with said fused sensor value; and providing an event responsecomprising at least one of: recording said fused sensor valuecorresponding to said event; recording a video from said imaging deviceoutput; communicating the event and/or the fused sensor value offboardthe vehicle via a telemetry device; and communicating the event and/orthe fused sensor value offboard the vehicle via a wide-area network. 22.The method of claim 21, which includes the steps of: providing a globalnavigation satellite system (GNSS) receiver including a GNSS antennamounted on said vehicle; providing an inertial measurement unit (IMU)mounted on said vehicle; connecting said GNSS receiver and said IMU tosaid computer processor; providing input signals to said computerprocessor from said GNSS receiver and said IMU corresponding togeospatial positions and attitudes of said vehicle; said computerprocessor calculating the location and orientation of said vehicle usingsaid GNSS receiver and said IMU signals; and said computer processorcombining said vehicle location and orientation information with saidextracted information to create said fused sensor value.
 23. A method ofacquiring information pertaining to the operation of a vehicle fromimages of objects of interest within the vehicle, including objects ofinterest on the instrument panel of the vehicle, which method comprisesthe steps of: providing at least one imaging device aboard said vehicle;providing a computer processor to control said imaging device;calibrating the imaging device with an adaptive imaging module;acquiring a test image of said object of interest with said adaptiveimaging module; identifying coordinates for said object of interest insaid test image; providing an object library comprising informationcorresponding to images of pre-identified objects corresponding tospecific types of vehicles; determining if an object of interest isincluded in the object library; selecting the vehicle type from saidobject library; if said object of interest is found in the objectlibrary, storing the object of interest configuration from said objectlibrary with said computer processor; if said object of interest is notfound in the object library, identifying and storing its configurationand operational characteristics with said computer processor; providingraw image data of objects of interest from said imaging device; applyinga low-pass filter to said raw image data to remove image noisetherefrom; using an edge detection algorithm for identifying points insaid image data at which the image brightness changes sharply or hasdetectable discontinuities; applying a binary hard limiter to convertedge-only images to binary images of said objects of interest; providingan output from said computer processor corresponding to a state of saidobjects of interest binary images; applying either a high-pass filter oran image differentiator to perform edge detection on said image data;using a set-up utility to create multiple individual fiducial images ofmultiple objects of interest; storing with said computer processor saidfiducial images; providing binary images of said objects of interestwith said imaging device; aligning said binary images detected by saidimaging device by comparing and cross-correlating said binary imageswith said fiducial images; using said set-up utility to create a featuremask for each individual object of interest; applying a mask to saidaligned binary images to isolate portions of said objects of interest;said imaging device providing an input to said computer processorcorresponding to said isolated portions of said objects of interest;said computer processor analyzing a state of said isolated portions ofsaid objects of interest and providing a corresponding output;determining states of the objects of interest using either: syntheticimages of the isolated portions of the objects of interest forcomparison with the masked binary images; or linear regressions to fitthe points (pixels) from the masked binary images to determine theobjects of interest states; providing configuration files for theobjects of interest with limits of travel of moving or changing parts ofthe objects of interest; determining operating conditions of the vehicleby comparing the objects of interest binary files with the configurationfiles; receiving geospatial data corresponding to a geospatial position,velocity or attitude of said vehicle; combining said geospatial datawith data from said imaging device corresponding to states of objects ofinterest in said vehicle to create fused sensor values; providing arules engine corresponding to operating characteristics of said vehicle;comparing with said computer processor said fused sensor values withsaid rules engine; detecting an exceedance(s) of said rules engine basedon said comparisons with said fused sensor values; and providing anevent response(s) comprising at least one of: recording said fusedsensor value corresponding to said event; recording a video from saidimaging device output; communicating the event and/or the fused sensorvalue offboard the vehicle via a telemetry device; and communicating theevent and/or the fused sensor value offboard the vehicle via a wide-areanetwork.
 24. A system for acquiring information from an image within avehicle, which system comprises: a software-controlled imaging devicemounted within said vehicle; said imaging device including individualraw pixel elements; a computer processor connected to and adapted forcontrolling said imaging device; said computer processor including amemory module; said imaging device capturing an image of said object ofinterest and providing imaging data as an input to said computerprocessor; said computer processor being adapted for storing saidimaging data in said memory module; said computer processor using saidimaging data to determine an image state of said vehicle and providingan output corresponding thereto; said imaging device includes advancedlight metering capabilities chosen from among the group comprising spotmetering, average metering and center-weighted average metering; andsaid computer processor being adapted for controlling said lightmetering capabilities.
 25. The system of claim 24 further comprising: arules engine executing on said computer processor and adapted foranalyzing said image state; and said computer processor being adaptedfor determining if said image state indicates that said vehicle is inviolation of a condition defined by said rules engine and initiating anappropriate response to said violation.
 26. The system of claim 25wherein said rules engine comprises aircraft flight profile rules asused by a flight operations quality assurance (FOQA) program.
 27. Themethod of claim 25 wherein said appropriate response includes at leastone of: sounding an aural alarm; displaying a visual alarm; andreporting the condition to an off-board station by means of a telemetrydevice.
 28. The system of claim 24 wherein said imaging device isadapted for using advanced light metering capabilities to capture animage and for applying said advanced light metering capabilitiesdirectly to raw pixel data before an image file is created.
 29. Thesystem of claim 24, which includes: an adaptive imaging module adaptedfor calibrating the imaging device; said adaptive imaging module beingadapted for acquiring a test image of an object of interest andidentifying coordinates for said object of interest in said test image.30. The system of claim 29, which includes: an object library stored insaid memory module and comprising information corresponding to images ofpre-identified objects of interest; means for determining if an objectof interest is included in the object library; means for storing theobject of interest configuration from said object library with saidcomputer processor if said object of interest is found in the objectlibrary; and means for identifying and storing its configuration andoperational characteristics with said computer processor if said objectof interest is not found in the object library.
 31. The system of claim30 wherein said object library includes pre-identified objects ofinterest corresponding to specific types of vehicles and said computerprocessor is adapted for selecting the vehicle type from said objectlibrary.
 32. The system of claim 24, which includes: said imaging devicebeing adapted for providing raw image data of an object of interest; alow-pass filter connected to said imaging device and adapted forremoving image noise from said role image data; said computer processorincluding an edge detection algorithm for identifying points in saidimage data at which the image brightness changes sharply or hasdetectable discontinuities; said computer processor including a binaryhard limiter adapted for converting an edge-only image to a binary imageof said object of interest; and said computer processor adapted forproviding an output corresponding to a state of said object of interestbinary image.
 33. The system of claim 32, which includes: a high-passfilter connected to said imaging device and adapted for performing edgedetection on said image data.
 34. The system of claim 32, whichincludes: an image differentiator connected to said imaging device andadapted for performing edge detection on said image data.
 35. The systemof claim 24, which includes: said computer processor being adapted for:creating and storing a fiducial image of an object of interest; saidimaging device being adapted for providing a binary image of said objectof interest; and said computer processor and adapted for aligning saidbinary image detected by said imaging device by comparing andcross-correlating said binary image with said fiducial image.
 36. Thesystem of claim 35, which includes: said computer processor beingadapted for applying a mask to said aligned binary image to isolate aportion of said object of interest; said imaging device being adaptedfor providing an input to said computer processor corresponding to saidisolated portion of said object of interest; and said computer processorbeing adapted for analyzing a state of said isolated portion of saidobject of interest and providing a corresponding output.
 37. The systemof claim 36, which includes: means for determining a state of the objectof interest using either: synthetic images of the isolated portion ofthe object of interest for comparison with the masked binary image; or alinear regression to fit the points (pixels) from the masked binaryimage to determine the object of interest state.
 38. The system of claim24, which includes: means for providing a configuration file for anobject of interest with limits of travel of a moving or changing part ofthe object of interest; and means for determining an operating conditionof the vehicle by comparing the object of interest binary file with theconfiguration file.
 39. The system of claim 24, which includes: a set-uputility adapted for creating a fiducial image comprising multipleindividual fiducial images of multiple objects of interest; and saidset-up utility being adapted for creating a feature mask for eachindividual object of interest.
 40. The system of claim 24, whichincludes: means for receiving geospatial data corresponding to ageospatial position, velocity or attitude of said vehicle; means forcombining said geospatial data with data from said imaging devicecorresponding to a state of an object of interest in said vehicle tocreate a fused sensor value; means for providing a rules enginecorresponding to operating characteristics of said vehicle; means forcomparing with said computer processor said fused sensor value with saidrules engine; means for detecting an exceedance of said rules enginebased on said comparison with said fused sensor value; and means forproviding an event response comprising at least one of: recording saidfused sensor value corresponding to said event; recording a video fromsaid imaging device output; communicating the event and/or the fusedsensor value offboard the vehicle via a telemetry device; andcommunicating the event and/or the fused sensor value offboard thevehicle via a wide-area network.
 41. The system of claim 40, furthercomprising: a global navigation satellite system (GNSS) receiverincluding a GNSS antenna, said receiver being mounted on or associatedwith said vehicle; an inertial measurement unit (IMU) mounted on saidvehicle; said GNSS receiver and said IMU being connected to saidcomputer processor and adapted for providing input signals theretocorresponding to geospatial positions and attitudes of said vehicle;said computer processor being adapted for calculating the location andorientation of said vehicle using said GNSS receiver and said IMUsignals; and wherein said location and orientation are combined withsaid extracted information to create a fused sensor value.
 42. Thesystem of claim 41 further comprising a rules engine executing on saidcomputer processing means, wherein said rules engine determines if saidfused sensor value indicates that said vehicle is in violation of acondition defined by said rules engine.
 43. The system of claim 42further comprising a telemetry device for transmitting said extractedinformation and said violation from said vehicle.
 44. The system ofclaim 24 wherein said image includes an object of interest comprising atleast a portion of the instrument panel of said vehicle.
 45. The systemof claim 44 wherein said at least a portion of said instrument panel isa feature selected from the group comprising: mechanical gauge, digitalreadout, status light, functional switch, and operator control.